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Estimating Criticality of Resting-State Phase Synchronization Network Based on EEG Source Signals

机译:基于脑电信号的静止状态相位同步网络的临界度估计

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EEG phase synchrony is an important signature in estimating functional connectivity of brain network, in which criticality of phase-locking state has been viewed as the key factor in facilitating dynamic reorganization of functional network. Based on source trace of resting-state EEG signals recorded from 24 subjects, this study extracted phase-locking intervals (PLIs) between pairwise source signals and constructed PLI sets with size higher than 105 for each subject, from frontal-parietal, frontal-temporal, and temporal-parietal cortical areas, respectively. Through further data fitting in power-law model, this study finds that θ- (4-8 Hz) and α-band (8-13 Hz) activities have longer phase-locking duration in a broader power-law distribution interval, compared to those in high frequency bands, indicating higher temporal stability of functional coupling between brain areas. In contrast, the probability density of PLIs oscillating in β (13-30 Hz) and γ (30-60 Hz) bands has less data fitting errors and bigger power-law exponent, suggesting higher criticality and flexibility of reorganization of phase synchronization networks. The findings are expected to provide effective neural signatures for comparison and recognition of neural correlations of cognition, emotion, disease etc. in the future.
机译:脑电相位同步是估计脑网络功能连通性的重要标志,其中锁相状态的重要性已被视为促进功能网络动态重组的关键因素。基于从24位受试者记录的静止状态EEG信号的源迹线,这项研究从额顶,额颞叶提取成对源信号之间的锁相间隔(PLI),并为每个受试者构建大小大于105的PLI集,和颞顶皮质区域。通过对幂律模型进行进一步的数据拟合,本研究发现,与更宽的幂律分布间隔相比,θ-(4-8 Hz)和α波段(8-13 Hz)活动具有更长的锁相持续时间。那些在高频段,表明大脑区域之间功能耦合的更高的时间稳定性。相比之下,在β(13-30 Hz)和γ(30-60 Hz)频带中振荡的PLI的概率密度具有较小的数据拟合误差和较大的幂律指数,这表明相同步网络的重组具有更高的关键性和灵活性。这些发现有望为将来的认知,情感,疾病等神经相关性的比较和识别提供有效的神经特征。

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